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        <a href="deepbelief-module.html">Package&nbsp;deepbelief</a> ::
        Module&nbsp;utils
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<h1 class="epydoc">Source Code for <a href="deepbelief.utils-module.html">Module deepbelief.utils</a></h1>
<pre class="py-src">
<a name="L1"></a><tt class="py-lineno"> 1</tt>  <tt class="py-line"><tt class="py-keyword">import</tt> <tt class="py-name">numpy</tt> <tt class="py-keyword">as</tt> <tt class="py-name">np</tt> </tt>
<a name="L2"></a><tt class="py-lineno"> 2</tt>  <tt class="py-line"> </tt>
<a name="L3"></a><tt class="py-lineno"> 3</tt>  <tt class="py-line"><tt class="py-name">__license__</tt> <tt class="py-op">=</tt> <tt class="py-string">'MIT License &lt;http://www.opensource.org/licenses/mit-license.php&gt;'</tt> </tt>
<a name="L4"></a><tt class="py-lineno"> 4</tt>  <tt class="py-line"><tt class="py-name">__author__</tt> <tt class="py-op">=</tt> <tt class="py-string">'Lucas Theis &lt;lucas@tuebingen.mpg.de&gt;'</tt> </tt>
<a name="L5"></a><tt class="py-lineno"> 5</tt>  <tt class="py-line"><tt class="py-name">__docformat__</tt> <tt class="py-op">=</tt> <tt class="py-string">'epytext'</tt> </tt>
<a name="L6"></a><tt class="py-lineno"> 6</tt>  <tt class="py-line"> </tt>
<a name="binary_numbers"></a><div id="binary_numbers-def"><a name="L7"></a><tt class="py-lineno"> 7</tt> <a class="py-toggle" href="#" id="binary_numbers-toggle" onclick="return toggle('binary_numbers');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="deepbelief.utils-module.html#binary_numbers">binary_numbers</a><tt class="py-op">(</tt><tt class="py-param">n</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="binary_numbers-collapsed" style="display:none;" pad="++" indent="++++"></div><div id="binary_numbers-expanded"><a name="L8"></a><tt class="py-lineno"> 8</tt>  <tt class="py-line">        <tt class="py-docstring">"""</tt> </tt>
<a name="L9"></a><tt class="py-lineno"> 9</tt>  <tt class="py-line"><tt class="py-docstring">        Generates an n x 2^n matrix whose columns are filled with binary-encoded</tt> </tt>
<a name="L10"></a><tt class="py-lineno">10</tt>  <tt class="py-line"><tt class="py-docstring">        numbers.</tt> </tt>
<a name="L11"></a><tt class="py-lineno">11</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L12"></a><tt class="py-lineno">12</tt>  <tt class="py-line"><tt class="py-docstring">        @type  n: integer</tt> </tt>
<a name="L13"></a><tt class="py-lineno">13</tt>  <tt class="py-line"><tt class="py-docstring">        @param n: number of bits</tt> </tt>
<a name="L14"></a><tt class="py-lineno">14</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L15"></a><tt class="py-lineno">15</tt>  <tt class="py-line"><tt class="py-docstring">        @rtype:  matrix</tt> </tt>
<a name="L16"></a><tt class="py-lineno">16</tt>  <tt class="py-line"><tt class="py-docstring">        @return: matrix filled with binary numbers</tt> </tt>
<a name="L17"></a><tt class="py-lineno">17</tt>  <tt class="py-line"><tt class="py-docstring">        """</tt> </tt>
<a name="L18"></a><tt class="py-lineno">18</tt>  <tt class="py-line"> </tt>
<a name="L19"></a><tt class="py-lineno">19</tt>  <tt class="py-line">        <tt class="py-keyword">def</tt> <tt class="py-def-name">recursive</tt><tt class="py-op">(</tt><tt class="py-param">B</tt><tt class="py-op">,</tt> <tt class="py-param">i</tt><tt class="py-op">=</tt><tt class="py-number">0</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L20"></a><tt class="py-lineno">20</tt>  <tt class="py-line">                <tt class="py-name">m</tt> <tt class="py-op">=</tt> <tt class="py-name">B</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt><tt class="py-op">[</tt><tt class="py-number">1</tt><tt class="py-op">]</tt> <tt class="py-op">/</tt> <tt class="py-number">2</tt> </tt>
<a name="L21"></a><tt class="py-lineno">21</tt>  <tt class="py-line"> </tt>
<a name="L22"></a><tt class="py-lineno">22</tt>  <tt class="py-line">                <tt class="py-name">B</tt><tt class="py-op">[</tt><tt class="py-name">i</tt><tt class="py-op">,</tt> <tt class="py-name">m</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-number">1</tt> </tt>
<a name="L23"></a><tt class="py-lineno">23</tt>  <tt class="py-line"> </tt>
<a name="L24"></a><tt class="py-lineno">24</tt>  <tt class="py-line">                <tt class="py-keyword">if</tt> <tt class="py-name">m</tt> <tt class="py-op">&gt;</tt> <tt class="py-number">1</tt><tt class="py-op">:</tt> </tt>
<a name="L25"></a><tt class="py-lineno">25</tt>  <tt class="py-line">                        <tt class="py-name">recursive</tt><tt class="py-op">(</tt><tt class="py-name">B</tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt> <tt class="py-op">:</tt><tt class="py-name">m</tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-name">i</tt> <tt class="py-op">+</tt> <tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
<a name="L26"></a><tt class="py-lineno">26</tt>  <tt class="py-line">                        <tt class="py-name">recursive</tt><tt class="py-op">(</tt><tt class="py-name">B</tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt> <tt class="py-name">m</tt><tt class="py-op">:</tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-name">i</tt> <tt class="py-op">+</tt> <tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
</div><a name="L27"></a><tt class="py-lineno">27</tt>  <tt class="py-line"> </tt>
<a name="L28"></a><tt class="py-lineno">28</tt>  <tt class="py-line">        <tt class="py-name">B</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">matrix</tt><tt class="py-op">(</tt><tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">[</tt><tt class="py-name">n</tt><tt class="py-op">,</tt> <tt class="py-name">pow</tt><tt class="py-op">(</tt><tt class="py-number">2</tt><tt class="py-op">,</tt> <tt class="py-name">n</tt><tt class="py-op">)</tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-string">'byte'</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L29"></a><tt class="py-lineno">29</tt>  <tt class="py-line">        <tt class="py-name">recursive</tt><tt class="py-op">(</tt><tt class="py-name">B</tt><tt class="py-op">)</tt> </tt>
<a name="L30"></a><tt class="py-lineno">30</tt>  <tt class="py-line">        <tt class="py-keyword">return</tt> <tt class="py-name">B</tt> </tt>
</div><a name="L31"></a><tt class="py-lineno">31</tt>  <tt class="py-line"> </tt>
<a name="L32"></a><tt class="py-lineno">32</tt>  <tt class="py-line"> </tt>
<a name="L33"></a><tt class="py-lineno">33</tt>  <tt class="py-line"> </tt>
<a name="logsumexp"></a><div id="logsumexp-def"><a name="L34"></a><tt class="py-lineno">34</tt> <a class="py-toggle" href="#" id="logsumexp-toggle" onclick="return toggle('logsumexp');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="deepbelief.utils-module.html#logsumexp">logsumexp</a><tt class="py-op">(</tt><tt class="py-param">x</tt><tt class="py-op">,</tt> <tt class="py-param">ax</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="logsumexp-collapsed" style="display:none;" pad="++" indent="++++"></div><div id="logsumexp-expanded"><a name="L35"></a><tt class="py-lineno">35</tt>  <tt class="py-line">        <tt class="py-docstring">"""</tt> </tt>
<a name="L36"></a><tt class="py-lineno">36</tt>  <tt class="py-line"><tt class="py-docstring">        Computes the log of the sum of the exp of the entries in x in a numerically</tt> </tt>
<a name="L37"></a><tt class="py-lineno">37</tt>  <tt class="py-line"><tt class="py-docstring">        stable way.</tt> </tt>
<a name="L38"></a><tt class="py-lineno">38</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L39"></a><tt class="py-lineno">39</tt>  <tt class="py-line"><tt class="py-docstring">        @type  x: array_like</tt> </tt>
<a name="L40"></a><tt class="py-lineno">40</tt>  <tt class="py-line"><tt class="py-docstring">        @param x: a list or a matrix of numbers</tt> </tt>
<a name="L41"></a><tt class="py-lineno">41</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L42"></a><tt class="py-lineno">42</tt>  <tt class="py-line"><tt class="py-docstring">        @type  ax: integer</tt> </tt>
<a name="L43"></a><tt class="py-lineno">43</tt>  <tt class="py-line"><tt class="py-docstring">        @param ax: axis along which the sum is applied</tt> </tt>
<a name="L44"></a><tt class="py-lineno">44</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L45"></a><tt class="py-lineno">45</tt>  <tt class="py-line"><tt class="py-docstring">        @rtype:  matrix</tt> </tt>
<a name="L46"></a><tt class="py-lineno">46</tt>  <tt class="py-line"><tt class="py-docstring">        @return: a matrix containing the results</tt> </tt>
<a name="L47"></a><tt class="py-lineno">47</tt>  <tt class="py-line"><tt class="py-docstring">        """</tt> </tt>
<a name="L48"></a><tt class="py-lineno">48</tt>  <tt class="py-line"> </tt>
<a name="L49"></a><tt class="py-lineno">49</tt>  <tt class="py-line">        <tt class="py-name">x</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">asmatrix</tt><tt class="py-op">(</tt><tt class="py-name">x</tt><tt class="py-op">)</tt> </tt>
<a name="L50"></a><tt class="py-lineno">50</tt>  <tt class="py-line">        <tt class="py-name">x_max</tt> <tt class="py-op">=</tt> <tt class="py-name">x</tt><tt class="py-op">.</tt><tt class="py-name">max</tt><tt class="py-op">(</tt><tt class="py-name">ax</tt><tt class="py-op">)</tt> </tt>
<a name="L51"></a><tt class="py-lineno">51</tt>  <tt class="py-line">        <tt class="py-keyword">return</tt> <tt class="py-name">x_max</tt> <tt class="py-op">+</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">log</tt><tt class="py-op">(</tt><tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">exp</tt><tt class="py-op">(</tt><tt class="py-name">x</tt> <tt class="py-op">-</tt> <tt class="py-name">x_max</tt><tt class="py-op">)</tt><tt class="py-op">.</tt><tt class="py-name">sum</tt><tt class="py-op">(</tt><tt class="py-name">ax</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
</div><a name="L52"></a><tt class="py-lineno">52</tt>  <tt class="py-line"> </tt>
<a name="L53"></a><tt class="py-lineno">53</tt>  <tt class="py-line"> </tt>
<a name="L54"></a><tt class="py-lineno">54</tt>  <tt class="py-line"> </tt>
<a name="logmeanexp"></a><div id="logmeanexp-def"><a name="L55"></a><tt class="py-lineno">55</tt> <a class="py-toggle" href="#" id="logmeanexp-toggle" onclick="return toggle('logmeanexp');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="deepbelief.utils-module.html#logmeanexp">logmeanexp</a><tt class="py-op">(</tt><tt class="py-param">x</tt><tt class="py-op">,</tt> <tt class="py-param">ax</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="logmeanexp-collapsed" style="display:none;" pad="++" indent="++++"></div><div id="logmeanexp-expanded"><a name="L56"></a><tt class="py-lineno">56</tt>  <tt class="py-line">        <tt class="py-docstring">"""</tt> </tt>
<a name="L57"></a><tt class="py-lineno">57</tt>  <tt class="py-line"><tt class="py-docstring">        Computes the log of the mean of the exp of the entries in x in a numerically</tt> </tt>
<a name="L58"></a><tt class="py-lineno">58</tt>  <tt class="py-line"><tt class="py-docstring">        stable way. Uses logsumexp.</tt> </tt>
<a name="L59"></a><tt class="py-lineno">59</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L60"></a><tt class="py-lineno">60</tt>  <tt class="py-line"><tt class="py-docstring">        @type  x: array_like</tt> </tt>
<a name="L61"></a><tt class="py-lineno">61</tt>  <tt class="py-line"><tt class="py-docstring">        @param x: a list or a matrix of numbers</tt> </tt>
<a name="L62"></a><tt class="py-lineno">62</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L63"></a><tt class="py-lineno">63</tt>  <tt class="py-line"><tt class="py-docstring">        @type  ax: integer</tt> </tt>
<a name="L64"></a><tt class="py-lineno">64</tt>  <tt class="py-line"><tt class="py-docstring">        @param ax: axis along which the values are averaged</tt> </tt>
<a name="L65"></a><tt class="py-lineno">65</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L66"></a><tt class="py-lineno">66</tt>  <tt class="py-line"><tt class="py-docstring">        @rtype:  matrix</tt> </tt>
<a name="L67"></a><tt class="py-lineno">67</tt>  <tt class="py-line"><tt class="py-docstring">        @return: a matrix containing the results</tt> </tt>
<a name="L68"></a><tt class="py-lineno">68</tt>  <tt class="py-line"><tt class="py-docstring">        """</tt> </tt>
<a name="L69"></a><tt class="py-lineno">69</tt>  <tt class="py-line"> </tt>
<a name="L70"></a><tt class="py-lineno">70</tt>  <tt class="py-line">        <tt class="py-name">x</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">asarray</tt><tt class="py-op">(</tt><tt class="py-name">x</tt><tt class="py-op">)</tt> </tt>
<a name="L71"></a><tt class="py-lineno">71</tt>  <tt class="py-line"> </tt>
<a name="L72"></a><tt class="py-lineno">72</tt>  <tt class="py-line">        <tt class="py-keyword">if</tt> <tt class="py-name">ax</tt> <tt class="py-keyword">is</tt> <tt class="py-name">None</tt><tt class="py-op">:</tt> </tt>
<a name="L73"></a><tt class="py-lineno">73</tt>  <tt class="py-line">                <tt class="py-name">n</tt> <tt class="py-op">=</tt> <tt class="py-name">x</tt><tt class="py-op">.</tt><tt class="py-name">size</tt> </tt>
<a name="L74"></a><tt class="py-lineno">74</tt>  <tt class="py-line">        <tt class="py-keyword">else</tt><tt class="py-op">:</tt> </tt>
<a name="L75"></a><tt class="py-lineno">75</tt>  <tt class="py-line">                <tt class="py-name">n</tt> <tt class="py-op">=</tt> <tt class="py-name">x</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt><tt class="py-op">[</tt><tt class="py-name">ax</tt><tt class="py-op">]</tt> </tt>
<a name="L76"></a><tt class="py-lineno">76</tt>  <tt class="py-line"> </tt>
<a name="L77"></a><tt class="py-lineno">77</tt>  <tt class="py-line">        <tt class="py-keyword">return</tt> <tt id="link-0" class="py-name" targets="Function deepbelief.utils.logsumexp()=deepbelief.utils-module.html#logsumexp"><a title="deepbelief.utils.logsumexp" class="py-name" href="#" onclick="return doclink('link-0', 'logsumexp', 'link-0');">logsumexp</a></tt><tt class="py-op">(</tt><tt class="py-name">x</tt><tt class="py-op">,</tt> <tt class="py-name">ax</tt><tt class="py-op">)</tt> <tt class="py-op">-</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">log</tt><tt class="py-op">(</tt><tt class="py-name">n</tt><tt class="py-op">)</tt> </tt>
</div><a name="L78"></a><tt class="py-lineno">78</tt>  <tt class="py-line"> </tt><script type="text/javascript">
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